Richmond, VA

Developer Jobs in Richmond, VA

25 jobs found

Include remote jobs

Today

Machine Learning Engineer 5 (Senior Manager, IC)

Capital One Richmond, VA

Richmond, VA

Today

$209k - $239k/yr Full time Manager Artificial Intelligence Big Data

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Job Description

Capital One’s Risk Tech team is partnering with the GRC team and company partners to build and deploy AI-powered, risk management solutions. In this onsite role in Richmond, VA, you’ll help design, build, scale, and operate machine learning models and multi-tenant platforms, with a focus on production monitoring and governed Responsible/Explainable AI.

Salary range: USD 209,000 - 238,500 per year (Richmond, VA). This role is eligible for performance-based incentive compensation, which may include cash bonus(es) and/or long-term incentives (LTI).

What You’ll Do

Design, build, and deliver ML models and components to solve real-world business problems in collaboration with Product and Data Science.
Build and scale massive multi-tenant platforms for large-footprint ML training and/or serving.
Apply ML modeling knowledge to inform infrastructure and approach decisions, including model choice, data and feature selection, training, hyperparameter tuning, dimensionality, bias/variance, and validation.
Address complex problems through application code, ML model development and validation, and automated tests and deployment.
Work within a cross-functional Agile team to create and enhance software for state-of-the-art big data and ML applications.
Retrain, maintain, and monitor ML models in production.
Use cloud-based architectures and platforms to deliver optimized ML models at scale.
Construct optimized data pipelines that feed ML models.
Apply CI/CD best practices, including test automation and monitoring, to support reliable deployment of ML models and application code.
Ensure code is well-managed to reduce vulnerabilities, maintain risk governance for models, and follow Responsible and Explainable AI best practices.
Use programming languages such as Python, Scala, or Java.

Requirements

Bachelor’s degree or higher in Computer Science, Machine Learning, or a related quantitative field (including Statistics, Economics, Operations Research, Analytics, Mathematics, or Engineering).
At least 6 years programming with Python, Java, Golang, or C++.
At least 6 years of ML experience using industry standard frameworks PyTorch or Tensorflow and libraries including Pandas, NumPy, Scikit-learn.
At least 6 years using and operating large-scale distributed systems such as Spark and Ray to prepare AI/ML data.
At least 4 years deploying and operating ML solutions in production, including operating production services in the cloud (AWS, GCP, Azure) and using Kubernetes to manage large-scale containerized ML systems.

Preferred Qualifications

Master’s or doctoral degree in computer science, electrical engineering, mathematics, or related field.
5+ years optimizing ML algorithms, configurations, and infrastructure.
5+ years following software development best practices including source control, testing, code reviews, and CI/CD.
5+ years building resilient software with pre-production testing, advanced deployment techniques (one-box, blue/green, gradual dial-up), monitoring and alarms, and preparing incident response plans.
5+ years working with ML techniques (Supervised, semi-supervised, and unsupervised, reinforcement learning) and model types (Regression, Classification, Clustering), along with architectures (RNNs, CNNs, LSTMs, Transformers) and evaluation and diagnosis (underfitting, overfitting).
5+ years designing, implementing, and scaling production-ready data pipelines for training and evaluating ML models.
ML industry impact through conference presentations, papers, blog posts, open source contributions, or patents.
Ability to communicate complex technical and machine learning concepts clearly to a variety of audiences.

Technologies You’ll Work With

Python, Scala, Java, Golang, C++, PyTorch, Tensorflow
Pandas, NumPy, Scikit-learn
Spark, Ray
AWS, GCP, Azure
Kubernetes

Benefits

Eligible for performance-based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI).
A comprehensive, competitive, and inclusive set of health, financial, and other benefits that support your total well-being.

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Today

Machine Learning Engineer 4

Capital One Richmond, VA

Richmond, VA

Today

$179k - $205k/yr Full time Application Security Artificial Intelligence Automation

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Job Description

Capital One’s Risk Tech team is building and deploying proprietary risk management solutions using modern AI. This onsite role in Richmond, VA focuses on designing, operationalizing, and monitoring machine learning models, along with the supporting infrastructure and production workflows that enable them at scale.

As a Machine Learning Engineer 4, you will contribute across the lifecycle: developing model components, implementing data and CI/CD pipelines, and ensuring models are maintained and governed for Responsible and Explainable AI.

What you’ll do

Conduct a range of ML engineering work, including designing, building, and/or delivering ML models and components to address real business problems in collaboration with Product and Data Science
Make ML infrastructure decisions based on practical experience with modeling techniques and common challenges, including model and data/feature selection, training, hyperparameter tuning, dimensionality, bias/variance, and validation
Solve complex technical problems by writing and testing application code, developing and validating ML models, and automating tests and deployment
Work in a cross-functional Agile team to build and improve software supporting big data and ML applications
Retrain, maintain, and monitor models in production
Leverage and/or build cloud-based architectures and platforms to deliver optimized ML models at scale
Build optimized data pipelines that supply ML models
Apply continuous integration and continuous deployment practices, including test automation and monitoring, to support reliable deployments of ML models and application code
Support strong engineering practices by managing code to reduce vulnerabilities, ensuring risk-governed model practices, and implementing Responsible and Explainable AI best practices
Use programming languages including Python, Scala, or Java

Minimum qualifications

Bachelor’s degree or higher in Computer Science, Machine Learning, or a related quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Engineering)
At least 4 years of experience programming with Python, Java, Golang, or C++
At least 4 years of Machine Learning experience using industry standard frameworks PyTorch or Tensorflow and libraries including Pandas, NumPy, Scikit-learn
At least 4 years of experience using and operating large scale distributed systems such as Spark or Ray to prepare AI/ML data
At least 2 years deploying and operating ML solutions in production, including operating production services in the cloud (AWS, GCP, Azure) and using Kubernetes to manage large scale containerized ML systems

Tools and technologies

Python, Scala, Java, Golang, C++
PyTorch, Tensorflow
Pandas, NumPy, Scikit-learn
Spark, Ray
AWS, GCP, Azure
Kubernetes

Compensation

Richmond, VA (onsite): USD 179,400 - 204,700 per year

Benefits

Comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being

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Today

Machine Learning Engineer 5

Capital One Richmond, VA

Richmond, VA

Today

$209k - $239k/yr Full time Artificial Intelligence Big Data Data Platform

Apply Now

Job Description

Capital One is hiring a Machine Learning Engineer 5 (onsite) in Richmond, VA to design, build, scale, deploy, and monitor ML models and platforms that address business needs.

Responsibilities

Design, build, and/or deliver ML models and components in collaboration with Product and Data Science teams
Build and scale massive multi-tenant platforms for large-footprint ML training and/or serving
Apply ML modeling expertise to guide infrastructure and modeling decisions, including model selection, data and feature selection, training, hyperparameter tuning, dimensionality, bias/variance, and validation
Solve complex problems by writing and testing application code, developing and validating ML models, and automating tests and deployment
Collaborate in a cross-functional Agile team to create and enhance software for big data and ML applications
Retrain, maintain, and monitor models in production
Use and/or build cloud-based architectures, technologies, and platforms to deliver optimized ML models at scale
Construct optimized data pipelines to supply ML models
Apply CI/CD best practices, including test automation and monitoring, to support successful deployment of ML models and application code
Ensure code is well-managed to reduce vulnerabilities, models are well-governed from a risk perspective, and ML follows Responsible and Explainable AI best practices
Use programming languages such as Python, Scala, or Java

Requirements

Bachelor’s Degree or higher in Computer Science, Machine Learning, or a related quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Engineering)
At least 6 years of experience programming with Python, Java, Golang, or C++
At least 6 years of Machine Learning experience using industry-standard frameworks PyTorch or Tensorflow and libraries (Pandas, NumPy, Scikit-learn)
At least 6 years operating large-scale distributed systems (Spark, Ray) to prepare AI/ML data
At least 4 years deploying and operating Machine Learning solutions in production, including operating production services in the cloud (AWS, GCP, Azure) and using Kubernetes for large-scale containerized ML systems

Technologies

Python, Scala, Java, Golang, C++
PyTorch, Tensorflow
Pandas, NumPy, Scikit-learn
Spark, Ray
AWS, GCP, Azure
Kubernetes
CI/CD, continuous integration, continuous deployment

Benefits

Performance-based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI)
Comprehensive, competitive, and inclusive set of health, financial and other benefits supporting total well-being

Preferred Qualifications

Master’s or doctoral degree in computer science, electrical engineering, mathematics, or related field
5+ years of experience optimizing ML algorithms, configurations, and infrastructure
5+ years following software development best practices including source control, testing, code reviews, CI/CD, etc.
5+ years building resilient software solutions with pre-production testing, advanced deployment techniques (one-box, blue/green, gradual dial-up), monitoring, alarms, and incident response plan preparation
5+ years working with ML techniques (Supervised, semi-supervised, and unsupervised, reinforcement learning, etc.), model types (Regression, Classification, Clustering, etc.), model architectures (RNNs, CNNs, LSTMs, Transformers), training concepts (loss function, hyperparameters, regularization), and evaluating model accuracy plus diagnosing and addressing underfitting and overfitting
5+ years designing, implementing, and scaling production-ready data pipelines for training and evaluating ML models
ML industry impact through conference presentations, papers, blog posts, open source contributions, or patents
Ability to communicate complex technical and machine learning concepts clearly to a variety of audiences

Location

Richmond, VA (onsite)

Compensation

USD 209,000 - 238,500 per year

Other

Capital One will consider sponsoring a new qualified applicant for employment authorization for this position
Applications may close after a minimum of 5 business days
No agencies please
Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws
Capital One promotes a drug-free workplace
Capital One will consider for employment qualified applicants with a criminal history consistent with applicable laws regarding criminal background inquiries
Accommodation for applicants available via Capital One Recruiting at 1-800-304-9102 or RecruitingAccommodation@capitalone.com
Technical support/questions about recruiting process: Careers@capitalone.com
Capital One does not provide, endorse, or guarantee third-party products, services, educational tools, or other information available through this site
Capital One Financial is made up of several different entities; postings may vary by country (Canada, United Kingdom, Philippines)

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5d ago

Snowflake Data Engineer

Cognizant Richmond, VA

Richmond, VA

5d ago

Up to $152k/yr Full time Artificial Intelligence Azure Data Engineer Cloud

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Job Description

Cognizant is hiring a hands-on Snowflake Data Engineer in Richmond, VA (onsite). This role focuses on strengthening data quality, data governance, metadata management, data lineage, and data catalog capabilities, with opportunities to accelerate lineage discovery and enrichment using AI/GenAI. The position offers a competitive annual salary of USD 152,000, plus participation in Cognizant’s discretionary annual incentive program.

What you’ll do

Design, develop, and implement data quality rules, including profiling, monitoring, and scorecards across enterprise data platforms.
Build and maintain data governance capabilities, such as business glossary management, metadata management, data catalogs, and lineage.
Automate lineage discovery and perform impact analysis as data changes.
Generate and recommend data quality rules, and enrich metadata and business definitions to improve consistency and usability.
Improve catalog search and support data asset discovery for relevant stakeholders.
Develop integrations between data quality/governance tools and platforms including Snowflake, Databricks, Azure Data Factory, SQL databases, and cloud storage.
Support MDM initiatives, including data stewardship and golden record management using tools such as Reltio.
Collaborate with data engineers, architects, and business stakeholders to implement governance and quality standards.
Analyze data issues, perform root cause analysis, and implement preventive controls.
Develop automation scripts and reusable frameworks to improve governance and quality operations.

Required qualifications

10+ years of experience in Data Quality, Data Governance, Metadata Management, or MDM.
Hands-on experience with a data quality platform such as DQ Labs, Ataccama, Informatica DQ, DQ Bigeye, Monte Carlo, Soda, or similar.
Experience with data catalog and lineage tools such as Microsoft Purview, Collibra, Alation, Informatica EDC, or similar.
Experience using AI/GenAI for metadata management, lineage generation, cataloging, and data quality rule creation.
Proficiency in SQL and Python.
Experience with cloud data platforms including ADF, Databricks, and Snowflake on Azure.
Understanding of data governance frameworks, data stewardship, business glossary, and data quality dimensions.
Bachelor’s degree in Computer Science, Information Systems Engineering, or a related field.

Technologies you may work with

DQ Labs, Ataccama, Informatica, DQ Bigeye, Monte Carlo, Soda
Microsoft Purview, Collibra, Alation, Informatica EDC
AI/GenAI, LLMs, LLM AI agents, Copilot technologies
SQL, Python, ADF, Databricks, Snowflake, Azure, Azure Data Factory
Reltio

Benefits

Medical/Dental/Vision/Life Insurance
Paid holidays plus Paid Time Off
401(k) plan and contributions
Long-term/Short-term Disability
Paid Parental Leave
Employee Stock Purchase Plan

Preferred skills

Experience with Reltio MDM or similar MDM platforms.
Experience implementing governance and quality controls in modern data lakehouse environments.
Exposure to LLMs, AI agents, Copilot technologies, or AI-powered governance solutions.
Knowledge of regulatory and compliance requirements related to data governance.

Salary and other compensation: The annual salary for this position is between $00–152K depending on experience and other qualifications of the successful candidate. This position is also eligible for Cognizant’s discretionary annual incentive program, based on performance and subject to the terms of Cognizant’s applicable plans.

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6d ago

Data Engineer 5 (Python, SQL, Databricks, Snowflake)

Capital One Richmond, VA

Richmond, VA

6d ago

$209k - $239k/yr Full time Artificial Intelligence Azure Data Engineer Big Data

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Job Description

Capital One is hiring a Data Engineer 5 to design and implement an AI-enabling data ecosystem on the Enterprise Platforms Technology team.

Responsibilities

Architect, build, and scale clean, reliable, latency-optimized data pipelines for both batch and real-time, supporting structured, semi-structured, and unstructured data for AI/ML and LLMs
Help define the architectural blueprint for the Top of House AI data layer
Act as a hands-on technical lead, mentoring junior and mid-level engineers on coding standards, design patterns, and engineering excellence
Partner with Enterprise Security and Data Governance to implement data classification, privacy safeguards, and automated lineage tracking for AI models and training datasets
Build and maintain feature stores that support real-time inferencing and offline model training for executive-facing predictive models
Audit and optimize cross-cloud data pipelines, query performance, and storage infrastructure to improve efficiency, cost management, and reliability
Collaborate with Technical Program Managers, Data Scientists, Top of House leads, and C-suite stakeholders to translate executive data needs into production-ready solutions

Requirements

Bachelor’s Degree or higher in Computer Science or a related quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Engineering)
6+ years of experience in application development (internship experience does not apply)
4+ years of experience in distributed data
4+ years of experience with SQL
4+ years programming with at least one: Python, Java, or Scala
4+ years designing and developing data pipelines
2+ years in data modeling and designing end-to-end data solutions using both relational and non-relational database systems

Technologies

Python, SQL, Databricks, Snowflake
Java, Scala
AWS, Microsoft Azure, Google Cloud

Preferred qualifications

Master’s Degree in a related field
9+ years of application development experience including Python, SQL, Scala, or Java
5+ years of experience with a public cloud (AWS, Microsoft Azure, Google Cloud)
5+ years working on real-time data and streaming applications
5+ years of data warehousing experience (for example, Snowflake)
Experience using interactive AI tooling to accelerate productivity, leveraging capabilities beyond basic code completion (Claude, Gemini)

Location

Richmond, VA (onsite)

Compensation

Annual salary range (full-time, Richmond, VA): USD 209,000 - 238,500
Other posted Data Engineer 5 salary ranges by location:
- McLean, VA: $229,900 - $262,400
- New York, NY: $250,800 - $286,200
- Plano, TX: $209,000 - $238,500
- Riverwoods, IL: $209,000 - $238,500

Incentives

Eligible for performance-based incentive compensation, which may include cash bonus(es) and/or long-term incentives (LTI)

Additional information

Applications are expected to be accepted for a minimum of 5 business days
No agencies
Equal Opportunity Employer (EOE), committed to non-discrimination in compliance with applicable federal, state, and local laws
Drug-free workplace
Capital One will consider qualified applicants with a criminal history in accordance with applicable law
Comprehensive, competitive, and inclusive health, financial, and other benefits to support total well-being

Accommodation and recruiting contact

Accommodation requests: 1-800-304-9102 or RecruitingAccommodation@capitalone.com
Technical support or recruiting process questions: Careers@capitalone.com

Entity note: Canada postings are for Capital One Canada; United Kingdom postings are for Capital One Europe; Philippines postings are for Capital One Philippines Service Corp. (COPSSC).

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6d ago

Data Engineer 4 (Manager, IC)

Capital One Richmond, VA

Richmond, VA

6d ago

$179k - $205k/yr Full time Manager Big Data Bigdata

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Job Description

Capital One is seeking a Data Engineer 4 (Manager, IC) in Richmond, VA to lead cloud-first data transformation work. The role focuses on designing, building, and supporting scalable data solutions, while applying engineering patterns, enforcing security standards, and coordinating across Agile teams.

Responsibilities

Collaborate with Agile teams to design, develop, test, implement, and support technical solutions across full-stack development tools and technologies
Influence a team spanning developers, data analysts, and data scientists with experience in machine learning, distributed microservices, lakehouse architecture, and full-stack systems
Develop solutions using Python and Spark, including open-source relational and NoSQL databases and cloud data warehousing platforms such as Databricks and Snowflake
Stay current with data technology trends through experimentation, learning, internal and external technology communities, and mentorship within the data community
Partner with product managers and software engineers to deliver robust cloud-first data solutions that support financial empowerment for millions of Americans
Independently design, build, and deliver cloud data solutions and applications with limited support from supervisors or managers
Architect and enforce common data engineering design patterns to support code quality, maintainability, and reuse across pipelines and platforms
Design and build data pipelines and platforms with scalability, resilience, and operational efficiency in mind, maintaining performance as data and business demands grow
Implement data security standards, including encryption at rest and in transit and fine-grained access control, to meet data privacy requirements
Serve as a data engineering ambassador, communicating technical concepts and outcomes clearly to internal and external stakeholders to support alignment

Required Qualifications

Bachelor’s Degree or higher in Computer Science or a related quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Engineering)
At least 4 years of experience in application development (internship experience does not apply)
At least 2 years of experience in distributed data
At least 2 years of experience with SQL
At least 2 years of experience with one programming language (Python, Java, or Scala)
At least 2 years of experience in data pipeline design and development
At least 1 year of experience in data modeling and designing end-to-end data solutions using both relational and non-relational database systems

Preferred Qualifications

7+ years of application development experience with demonstrated proficiency in Python, SQL, Scala, or Java
4+ years of hands-on experience designing, deploying, and operating data workloads in at least one public cloud environment (AWS, Microsoft Azure, or Google Cloud)
4+ years of experience building or supporting distributed data or compute workloads using tools such as EMR, Spark, Glue, or Databricks
4+ years of experience designing, implementing, and operating real-time or streaming data pipelines
2+ years of experience in data observability (e.g., Monte Carlo, Splunk) or data orchestration tools (e.g., Airflow, Dagster)
4+ years of experience working with unstructured or semistructured data using NoSQL databases (e.g., MongoDB, Cassandra, DynamoDB)
4+ years of experience designing and supporting data warehousing solutions (e.g., Snowflake, Redshift)
2+ years of experience working in an Agile development environment
2+ years of experience developing user-centric reusable data products

Technologies

Python, Spark, Scala, Java
Databricks, Snowflake
SQL, EMR, Glue, Airflow, Dagster
NoSQL, MongoDB, Cassandra, DynamoDB
Redshift
Monte Carlo, Splunk
AWS, Microsoft Azure, Google Cloud
Relational databases
Encryption at rest, encryption in transit, fine-grained access control

Salary, Location, and Incentives

Location: Richmond, VA (onsite)
Salary: USD 179,400 - 204,700 per year
Eligible for performance-based incentive compensation, which may include cash bonus(es) and/or long-term incentives (LTI)

Capital One also offers a comprehensive, competitive, and inclusive set of health, financial, and other benefits that support total well-being.

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7d ago

Senior Data Engineer – Generative AI

Astyra Corporation Richmond, VA

Richmond, VA

7d ago

$66 - $71/hr Full time Backend Developer Senior AI

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Job Description

Build a data reconciliation capability that bridges legacy and modernized platforms, combining data engineering with hands-on Generative AI.

Responsibilities

Design and develop a data reconciliation utility to compare data between legacy systems and modernized platforms
Create mechanisms to surface discrepancies, patterns, anomalies, and nuanced differences across large datasets
Use Generative AI alongside pattern matching and regex (and related techniques) to improve reconciliation accuracy
Deliver hands-on implementations using Python and modern Generative AI frameworks
Integrate with and consume external services via Model Context Protocol (MCP)
Build agentic or workflow-based solutions using LangGraph
Work closely with senior engineers and architects to design and accelerate development of the reconciliation platform
Develop scalable, maintainable data engineering solutions that support broader modernization initiatives
Participate in data validation, testing, troubleshooting, and production implementation
Support evolving data engineering initiatives as the reconciliation solution matures

Requirements

7+ years of experience in data engineering, software engineering, or a related technical discipline
Strong hands-on background in data engineering
Demonstrated experience building Generative AI solutions
Strong Python development skills
Hands-on experience with LangGraph or similar agentic AI frameworks
Experience working with Model Context Protocol (MCP), including consuming MCP services
Experience developing solutions involving data comparison, reconciliation, pattern detection, or data validation
Strong understanding of data processing and transformation concepts
Experience delivering production-quality solutions within modern CI/CD environments
Strong problem-solving skills and ability to work independently in a hands-on engineering role

Technologies

Python
LangGraph
Model Context Protocol (MCP)
Generative AI
regex
CI/CD

Preferred Qualifications

Experience supporting large-scale technology or data modernization initiatives
Experience in financial services or other highly regulated environments
Experience developing AI-enabled data engineering utilities or automation solutions
Familiarity with Spark or other distributed data-processing technologies
Prior experience within a large enterprise engineering environment